Construction and Calibration of an Exposure Matrix for the Welding Trades
Bibliographic record
Abstract
OBJECTIVES: This study aimed to construct, validate, and calibrate an exposure matrix that would be used to estimate personal airborne exposures to total dust, manganese, nickel, chromium, and aluminum for welders in the WHAT-ME cohort. The Workers' Health in Apprenticeship Trades: metal and electrical (WHAT-ME) study established a cohort of women and men welders to investigate pregnancy and other birth outcomes along with health issues related to welding. To construct the matrix, data were extracted and assembled from the literature and analyzed to produce exposure models. Final models derived in this first step were then compared with external data gathered under controlled conditions and later combined to form calibrated models. METHODS: A systematic literature search was conducted to identify and extract all relevant data from published journal articles appearing in selected databases. Summary data were extracted that represented airborne personal exposures to total, inhalable and respirable dusts along with metal concentrations for manganese, nickel, chromium, and aluminum. Mathematical exposure models were derived and a validation of the models undertaken in the second part of this study. The most common welding combinations of welding process, base metal, and consumable (welding scenarios) for welders taking part in the WHAT-ME study were identified through detailed welding questionnaires completed by WHAT-ME participants. These were replicated under controlled conditions with a welder equipped with a personal air sampling pump to gather samples. A gravimetric analysis was performed to determine total dust exposures followed by a metals analysis using ICP-MS. Predictions were made for these welding scenarios replicated in the laboratory, using the exposure models derived in the literature and the predictions correlated against the results from the welding laboratory replications. RESULTS: The systematic review yielded 92 published articles from which 737 summary statistics were extracted representing 4620 personal samples of total dust, 4762 of manganese, 4679 of nickel, 3972 of chromium, and 676 of aluminum. The highest total dust exposures were for flux-core arc welding (FCAW) while the highest manganese producing base metal was mild steel. For nickel, the highest emissions were from high alloyed steel using gas metal arc welding while chromium emissions were most abundant in manual metal arc welding on stainless steel. Aluminum exposures were highest in FCAW welding and on aluminum as a base metal. The replication of 21 scenarios covered more than 90% of the scenarios in the WHAT-ME study. Sixty-one laboratory welding sessions took place with a minimum of two replications per scenario. Spearman rank correlations between predicted exposures and mean measured exposures yielded a rho of 0.93 (P < 0.001) for total dust, 0.87 (P < 0.001) for manganese, 0.54 (P < 0.024) for nickel, 0.43 (P = 0.055) for chromium, and 0.29 (P = 0.210) for aluminum. CONCLUSIONS: This study produced the first welding exposure matrix composed of process, base metal, and consumable. This model was able to predict exposures observed under controlled conditions and could be used by any researcher to estimate welding exposures in a wide range of occupational contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".